1. Field of the Invention
The present invention relates to an information recommendation device and an information recommendation method configured to effectively detect and present a document, which is continued from a document browsed by a user in the past, from a document having data and time information as an attribute.
2. Description of the Related Art
Conventionally, various techniques have been developed so as to meet an important need as regards recommending and recognizing topics based on their appeal to users. For instance, in the World Wide Web (WWW), a technique exists which recommends other Web pages related to Web pages included in a browsing history and marked of “interested” for each user, and a technique exists which recommends goods purchased by other users who also purchased goods that the user is interested in.
A means for recommending information based on the user's interest includes, as a rough classification, a form of recommendation by collaboration filtering and a form of recommendation of analogous content items and of the same category. For instance, a technique which tries to predict an evaluation value in a collaboration filtering method is disclosed in JP-A 2003-167901 (KOKAI). Information recommendation based on characteristic vector matching for user's preferences is attempted in JP-A 2006-190128 (KOKAI). This technique, for example, extracts a plurality of characteristic keywords from a document set that is a user's use history, stores these keywords as characteristic vectors, and determines whether or not new content items are content items close to the user's preferences on the basis of whether or not the new content items are similar to the characteristic vectors.
However, as regards the collaboration filtering described in JP-A 2003-167901 (KOKAI), it is needed to use histories of other users in order to perform matching. For instance, in a case in which a content item is recommended for a user A who is interested in a certain topic, the filtering retrieves another user, user B, who is also interested in this topic, and decides a content item to be recommended to the user A based on the content use history of the user B. This kind of technique described in JP-A 2003-167901 (KOKAI) cannot be used in an operation which does not refer (or which is incapable of referring) to the use histories of other users.
In such a system described in JP-A 2006-190128 (KOKAI), based on use histories and preferences of users, in a case in which keywords do not directly coincide with one another like a case in which the same topics are represented by different keywords, a problem such that content items may not be recommended is posed. Even in a case of recommendation based on a category, a case in which a range of a topic showing the category and a range of a user's interest do not coincide with each other may pose a problem.
Further, it comes into question that the foregoing system may not trace a process or a transition of content items in a category as a common topic.